Loading and preprocessing the data

# Required Packages: 
# dplyr
# data.table
# ggplot2
# plotly

# Load compressed data:
raw.data <- read.csv(unzip('./activity.zip'))

# Process data by converting date to POSIX:
processed.data <- raw.data %>% mutate(
  interval = sprintf('%04d',interval), # Pad leading zeros
  dateTime = as.POSIXct(paste0(date,' ',interval), format="%Y-%m-%d %H%M"),
  date=as.Date(date, format="%Y-%m-%d"),
  )

What is mean total number of steps taken per day?

## Mean Total Number of Steps Per Day: 37.3825995807128
## Median Total Number of Steps Per Day: 0

What is the average daily activity pattern?

## Interval (5-min) Containing Max Steps: 0835

Imputing missing values

## Total Number of Missing Values (NA): 2304
## To approximate missing values, use the mean value for the 5-minute interval

## Mean Total Number of Steps Per Day (corrected): 37.3825995807128
## Median Total Number of Steps Per Day (corrected): 0
## Inputting Missing Data INCREASED total number of daily steps:  ( 656737.5  vs.  570608 )

Are there differences in activity patterns between weekdays and weekends?